AI Compliance Monitoring and Regulatory Intelligence

We configure monitoring for the specific agencies relevant to your business. Typical bank coverage includes OCC, FDIC, Federal Reserve, CFPB, FinCEN, SEC, CFTC, state banking and insurance departments across your operating geography, and FFIEC. Healthcare coverage includes CMS, HHS OCR, state medical boards, and DEA. Our current deployments cover 40+ distinct federal and state sources. If a source has a structured feed (RSS, API, XML), we integrate in days. If it requires scraping, we build a Playwright scraper with monitoring. We do not sell a generic feed. Every deployment is configured for your actual regulatory exposure.

We build a materiality framework during onboarding that encodes your business lines, product types, customer segments, geographic operations, risk appetite, and enforcement history. The framework is a scoring rubric with weighted factors. The materiality agent applies the rubric to each new regulatory item and produces a score and explanation. The first 4-6 weeks involve calibration: your team reviews borderline items, the rubric is adjusted, the false-positive and false-negative rates are tracked. After calibration, we see 88-94% agreement between the agent's score and the compliance team's judgment, with explicit reasoning on every disagreement so the framework keeps improving.

Yes. We have live integrations with ServiceNow GRC, MetricStream, RSA Archer, AuditBoard, Workiva, and LogicGate via their REST APIs. Action items, gap findings, and policy update recommendations flow into your existing workflow. Your team continues to use the tool they already know. If you do not have a GRC platform, we build a lightweight tracking workflow into the system itself using Postgres and a simple web UI. Moving to a dedicated GRC platform later is a matter of enabling the integration and migrating open items.

Every classification includes a structured explanation: which factors drove the score, what business lines it considered, and what it did not. Your team reviews a sample of below-threshold items weekly during the first 90 days, and can override any classification. Overrides write back to the training signal and adjust the materiality framework. We intentionally set the initial threshold conservative to err toward flagging. False positives are a small cost in review time. False negatives (missing a material rule) are the risk we design against. The audit log makes it clear when the agent saw an item and how it scored, which is important for examiner conversations about coverage.

Every item that scores in a middle band (0.6 to 0.8 on a 0-1 materiality scale) routes to a human for adjudication with the agent's full reasoning attached. Items that fall outside your defined business lines or jurisdictions route to a compliance lead rather than being silently dropped. Novel enforcement actions, consent orders, and court decisions that imply new interpretations of existing rules are flagged explicitly with a 'novel interpretation detected' tag. The agent does not pretend confidence on edge cases. It surfaces them with its reasoning and lets a human decide.

Every agent action writes to an append-only Postgres log with SHA-256 hash chaining to prevent tampering. Entries include timestamp, input source, full item text, classification, materiality score and reasoning, policy matches, gap analysis output, action items created, owner assignments, and every human override. Auditors access the log through a read-only view with filters for date range, regulator, business line, and status. We export to CSV, Parquet, or direct API push into AuditBoard or Workiva. Several of our clients have walked OCC examiners through the log directly on a screen share and closed coverage questions in a single meeting.

Three things. First, a clean policy library with owners and regulatory citations. If your 340 policies map to regulations loosely or not at all, we run a policy reconciliation sprint before going live (3-4 weeks). Second, the materiality framework: your team defines business lines, jurisdictions, product types, and scoring weights. We provide a template that covers 80% of common scenarios. Third, access: read/write API tokens for your GRC platform, read access to historical rule tracking for calibration, and read access to any licensed feeds you want to include (Westlaw, Bloomberg Law, Reg Alert). Total prep work runs 4-6 weeks in parallel with technical build.

We run 90 days of parallel operation. Your analysts continue their manual monitoring on the existing cadence. The agent runs alongside and produces its own daily brief. At end of each week, we compare the two: what the agent flagged that analysts missed, what analysts caught that the agent didn't score high enough, and every disagreement on materiality. The comparison data tunes the framework and builds team confidence. After 90 days, most teams transition to the agent as the primary source with manual review of its output rather than independent manual monitoring. The Reg Alert or equivalent subscription usually gets canceled in year two.